In the business environment today, especially for business sectors in which products are technologically complex and expensive, corporations must collect and efficiently use large amounts of data in order to maximize sales. Customer's needs have become more diverse, product lines have become more varied, and competitors have become more numerous. Therefore, it is important when attempting to sell complex products to a particular customer to provide the customer with accurate information that relates to their specific needs and shows how well various products meet those needs. For example, if a salesperson is able to present information to a prospect that distinguishes the salesperson's product from the competition in exactly the areas of interest to the prospect, the salesperson is more likely to make the sale. Technology enabled selling (“TES”) has evolved to provide various tools and techniques to aid salespersons in obtaining useful sales information. For example, several sales force automation (“SFA”) tools exist. In general, most of these SFA tools allow collection data of interest in a database and access to the database to obtain or generate sales information.
Current TES products have several important limitations. For example, very few TES applications assist the “in-the-trenches” salesperson with the actual job of selling. Those that do have some functionality for the salesperson are very inflexible and may not be helpful in situations that are not well adapted to the kind of information provided by the tool. Most current TES products lack functionality for supporting product positioning, competitor differentiation, feature-advantage-benefit discussion, and opportunity qualification. Those current TES products that provide some of the functionalities listed provide only a limited subset and provide it in an inflexible way, limiting its usefulness for the salesperson. For example, some current TES products aid in sales proposal generation or presentation generation, yet one product does not allow for generation of more than one type of document. Another disadvantage of these products is that the documents produced are basically inflexible templates that are populated by data in a predetermined way such that minimal or no salesperson knowledge is allowed to influence the kind of information produced. Therefore, important data known to the salesperson, such as special requirements or desires of a specific customer, might not be taken into account in producing documents. Some existing TES products may help salespersons to respond to product and competitive issues, but the salesperson is still left with considerable responsibilities to close the deal. For example, the salesperson must still finish the sales job by gathering validating customer stories, supporting analyst quotes, and value propositions. These must all then be and presented to the sale prospect in a manner consistent with the prospect's business needs and level in the company.
Historically, TES tools use a relational database to store either “aggregatable” data (repeating data records), or “related data points.” An example of aggregatable data would be a retail store database full of sales transactions. An example of related data points would be an order entry database: one customer has many orders, each order many items, each item many data points (price, size, color, etc.). Although relational database management systems (“RDBMSs”) can represent complex relationships between types of items or objects, they are frequently overlooked for their ability to represent relationships between concepts and ideas. For example, an animals database may link predators to prey through a “many-to-many” relationship table. In general, however, TES databases are typically used to store “business facts” rather than to represent linked ideas. For this reason, current TES tools are relatively rigid and have low levels of “intelligence”. Thus, current TES tools do little to help a technology salesperson in the task of appropriately positioning a product or service given a customer's unique and industry-specific business requirements, their key concerns/objections, and the known competitors.
The vast majority of sales opportunities are lost because of inappropriate product positioning and incomplete or inaccurate competitive differentiation. Features that are not applicable to a customer's requirements may distract decision-makers and even provide an opportunity to raise objections. For example, many deals fail because what a vendor calls a feature may actually be a liability given the idiosyncrasies of an organization. Highlighting competitive weaknesses that don't apply in a particular industry will certainly not sway (and may potentially alienate) educated decision markers.
The static documents produced by current TES tools fail to address the ever-changing, situational characteristics of the sales context. Generic product marketing literature, competitive matrices, competitive white papers, standard presentations and other static selling tools are highly imprecise and often potentially damaging if they lack context-sensitivity to a customer's specific situation. Automatic generation of simple web pages, sales proposals, or presentations based on a customer's specific situation exists in some products. However, typical TES products cannot dynamically generate highly context-specific correspondence, white papers, qualification tools, sales strategy worksheets, and competitive matrices.